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報  告 人：程濤  教授，University College London，UK 

報告題目：Network complexity and Spatio-temporal data mining

時        間：8月7日上午10點

地        點：中國科學院地理科學與資源研究所 2321會議室

報告簡介: 

    Modelling of spatio-temporal network data presents a unique set of problems as they often exhibit spatio-temporal dependence, nonlinearity and heterogeneity. There are two fundamental challenges to modelling the complexity of networks. One challenge is to model dependency in both space and time seamlessly and simultaneously. Another challenge is to fully accommodate the topology (links and hierarchies) and geometry (distances and directions) of the networks. This presentation will report the progress made in tackling these challenges through innovative combination of novel machine learning methods with advanced statistical approaches, drawing upon concepts from network complexity and data mining. It will demonstrate the procedures that integrate spatio-temporal prediction, pattern detection, simulation, and visualization for analysing traffic data and crime data in Central London.

 http://standard.cege.ucl.ac.uk) is funded by EPSRC (2009-12) in partnership with Transport for London (TfL). Using real-time traffic data, STANDARD presents an innovative approach to integrated space-time analysis of traffic, using concepts from network complexity and spatio-temporal data mining. Most recently, she led the successful bid for the CPC (Crime, Policing and Citizenship) project (PI, EPSRC 2012-15, ￡1,400,235) addressing the aims of RCUK’s Global Uncertainties Programme on crime, terrorism and ideologies and beliefs (www.ucl.ac.uk/cpc). It draws upon a broad-spectrum of expertise in four departments across two facilities in UCL. There are 4 PDRAs and several PhD students working on the CPC project. 

報告人簡介:

    Tao Cheng: Professor of Geoinformatics, Dept of Civil, Environ & Geomatic Eng, Faculty of Engineering Science. She has studied and lectured in China, the Netherlands, Hong Kong, France and the UK. She has broad knowledge and experience in Geographic Information Sciences (GISc), from data acquisition, to information processing, management and analysis, with applications in environmental monitoring, natural resource management, health, transport and crime studies. She has over 140 publications and is a past recipient of the U. V. Helava Award for the best paper in the ISPRS Journal of Photogrammetry and Remote Sensing. Her research interests span network complexity, integrated spatio-temporal data mining (prediction, clustering, visualization and simulation), Geocomputation, and uncertainty and quality of geographic information. She currently leads the first attempt to mine complex real-time spatio-temporal transport network data in Central London: STANDARD (Spatio-Temporal Analysis of Network Data And Route Dynamics (